%0 Journal Article
%T Hybrid Integration of Taguchi Parametric Design, Grey Relational Analysis, and Principal Component Analysis Optimization for Plastic Gear Production
%A Nik Mizamzul Mehat
%A Shahrul Kamaruddin
%A Abdul Rahim Othman
%J Chinese Journal of Engineering
%D 2014
%R 10.1155/2014/351206
%X The identification of optimal processing parameters is an important practice in the plastic injection moulding industry because of the significant effect of such parameters on plastic part quality and cost. However, the optimization design of injection moulding process parameters can be difficult because more than one quality characteristic is used in the evaluation. This study systematically develops a hybrid optimization method for multiple quality characteristics by integrating the Taguchi parameter design, grey relational analysis, and principal component analysis. A plastic gear is used to demonstrate the efficiency and validity of the proposed hybrid optimization method in controlling all influential injection moulding processing parameters during plastic gear manufacturing. To minimize the shrinkage behaviour in tooth thickness, addendum circle, and dedendum circle of moulded gear, the optimal combination of different process parameters is determined. The case study demonstrates that the proposed optimization method can produce plastic-moulded gear with minimum shrinkage behaviour of 1.8%, 1.53%, and 2.42% in tooth thickness, addendum circle, and dedendum circle, respectively; these values are less than the values in the main experiment. Therefore, shrinkage-related defects that lead to severe failure in plastic gears can be effectively minimized while satisfying the demand of the global plastic gear industry. 1. Introduction Injection moulding is a complex process because of its requirements for numerous delicate adjustments. The quality of an injection-moulded part significantly depends on the selection of appropriate materials, parts, mould designs, and processing parameters. A review of previous works shows that the setting of processing parameters significantly affects the quality of plastic parts [1, 2]. The selection of injection moulding process parameters previously involves a trial-and-error method [3]. However, obtaining an optimal parameter setting for complex-manufacturing processes is difficult because the trial-and-error method is a ¡°one change at a time¡± test [4]. This tuning exercise is repeated until the quality of the moulded part is found satisfactory, thus incurring high production costs and long setup times [5]. Moreover, the adjustments and modifications of processing parameters rely heavily on the experience and intuition of the moulding personnel [6]. Nevertheless, the growing demand in the industry for expert moulding personnel exceeds the supply; moreover, amateur moulding personnel require more than 10 years of
%U http://www.hindawi.com/journals/cje/2014/351206/